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Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long history of their successful use in revealing the importance of various members of the network. However, modeling of covert, terrorist or criminal networks through social graph dose not really provide the hierarchical structure which exist in these networks as these networks are composed of leaders and followers etc. In this research we analyze and predict the most likely role a particular node can adapt once a member of the network is either killed or caught. The adaptation is based on computing Bayes posteriori probability of each node and the level of the said node in the network structure. [ABSTRACT FROM AUTHOR]

The investigation presented here compares the advantage of using a Kalman filter as opposed to an alpha-beta filter for multi-target tracking systems. The former is often used to speed up the computation time. However, it is shown here that due to the difficulty of data association the benefits are not as good as might be expected based on their relative results from single target tracking case. Extensive analyses are performed by selecting various scenarios where the correlation factor affects the performance of alpha-beta filter. [ABSTRACT FROM AUTHOR]

The research presents a simulation study on the performance of a target tracker using a critical angle selection technique for optimal correlation assignment of a target track with the incoming observation(s) for the track splitting filter (TSF) algorithm. In a typical TSF all the observations falling inside a likelihood ellipse are used for update. However, our proposed optimal correlation procedure TSF algorithm uses only those observations for track update that fall within the critical angle sector made inside the prediction ellipse. This kind of approach is particularly important if the computational and memory requirements are limited relative to the amount of input data (number of objects) that can potentially saturate the system. Previous performance work [1] has been done on specific (deterministic) scenarios. One of the reasons for considering the specific scenarios, which were normally crossing targets, was to test the efficiency of the track splitting algorithm. This approach gives a measure of performance for a specific, possibly unrealistic scenario. However, such investigation procedures help in designing tracking systems that can select high-value targets based on particular attributes. In order to develop procedures that would enable a more general performance assessment compared with deterministic scenarios, our study adopted a random target motion scenario. Its implementation for testing the proposed technique using a track splitting Kalman filter algorithm is investigated. A number of performance parameters that give the activity profile of the tracking scenario are also investigated. This kind of performance evaluation can provide in-depth knowledge of tracking activity for developing possibly better and more appropriate target tracking systems. The complete prototype system is implemented using a TMS320C6416 digital signal processor (DSP). [ABSTRACT FROM AUTHOR]

Abstract: The paper presents a simulation study on the performance of a target tracker using controlled selection paring for a track splitting filter algorithm. In a typical track splitting filter all the observation which fall inside a likelihood ellipse are used for update, however, in our proposed controlled selection paring procedure track splitting filter (TSF) algorithm uses maximum of two observations for track update. This kind of approach is particularly important if the computational and memory requirement is limited in comparison to the amount of input data (number of objects) that can saturate the system. Much of the previous performance work has been done on specific (deterministic) scenarios [1]. One of the reasons for considering the specific scenarios, which were normally crossing targets, was to test the efficiency of the track splitting algorithm for different situations. However, this approach only gives a measure of performance for a specific, possibly unrealistic, scenario and it was felt appropriate to develop procedures that would enable a more general performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the proposed controlled track splitting algorithm using Kalman filters is investigated through a number of performance parameters which gives the activity profile of the tracking scenario. This kind of performance evaluation can provide a guide line for developing appropriate tracking systems of various categories. The complete proto type system is implemented using a TMS320C6416 DSP. [ABSTRACT FROM AUTHOR]